Energia- ja konetekniikan laitos

Energian konversio ja energiajärjestelmät

Energian konversion ja energiajärjestelmien tutkimusryhmä konetekniikan laitoksella.

Lisätietoja tutkimusryhmän toiminnasta saatavilla englanninkielisellä sivulla.

Advanced experimental flow and combustion diagnostics

Department of Energy and Mechanical Engineering

Our main focus is modelling energy applications with CFD

Department of Energy and Mechanical Engineering

Modern energy systems research focuses on finding optimal solutions for ensuring a comfortable and healthy indoor environment while minimizing energy use. This is achieved both by utilizing computer simulation and optimization and by conducting experimental research on novel technologies.

Department of Energy and Mechanical Engineering

In the energy storage team, we work with a large variety of different energy storage technologies to support the transition to renewable energy production.

Department of Energy and Mechanical Engineering

We focus on large-scale energy systems, integrated assessment models, industrial energy systems and simulation and optimization techniques

Department of Energy and Mechanical Engineering

We aim to optimize wind turbine technologies, energy system and energy storage couplings, and siting strategies to increase the overall contribution of wind energy to the global energy mix.

Department of Energy and Mechanical Engineering

We focus on methanol synthesis and hydrogen production.

Department of Energy and Mechanical Engineering

Ammonia as a sustainable fuel

Qiang Cheng, Akram Muhammad, Ossi Kaario, Zeeshan Ahmad, Larmi Martti 2025 Renewable and Sustainable Energy Reviews

Reducing district heating carbon dioxide emissions with data center waste heat – Region perspective

Seela Tervo, Sanna Syri, Pauli Hiltunen 2025 Renewable and Sustainable Energy Reviews

Gas evolution in self-extinguishing and insulative nanopolysaccharide-based hybrid foams

Roozbeh Abidnejad, Daria Robertson, Alexey Khakalo, Morteza Gholami Haghighi Fard, Ari Seppälä, Eva Pasquier, Blaise Tardy, Bruno Dufau Mattos, Orlando Rojas Gaona 2024 Carbohydrate Polymers

Analysis of machine learning models and data sources to forecast burst pressure of petroleum corroded pipelines : A comprehensive review

Afzal Ahmed Soomro, Ainul Akmar Mokhtar, Hilmi B Hussin, Najeebullah Lashari, Temidayo Lekan Oladosu, Syed Muslim Jameel, Muddasser Inayat 2024 Engineering Failure Analysis